FutureLearn Week 3: Post 2 of 3

Real-life examples of environmental analytics

A real life example of citizen science analysing the environment is that it can contribute to better and more accurate evaluations of human infrastructures in wildlife such as recording roadkill accidents so that it can be made available to emphasise how much roads can impact wildlife.

Comments

FutureLearn Week 2: Post 1 of 4

Open data has been increasing for some time now with data being made open on various sites globally. There are many advantages to having open data, these advantages include being able to share public data sets so that they can be compared. These open data sources can also be used for environmental purposes or even health issues. Disadvantages of open data would include the fact that the site providing the data would be inherently biased and formed in the opinion of the creator.

Post #1: Definition of Big Data

Big Data is a term that is used to describe a massive volume of both structured and unstructured data that is so large it is difficult to process using traditional database and software techniques. In most enterprise scenarios the volume of data is too big or it moves too fast or it exceeds current processing capacity. Big Data comes from text, audio, video, and images. Big Data is analysed by organisations and businesses for reasons like discovering patterns and trends related to human behaviour and our interaction with technology, which can then be used to make decisions that impact how we live, work , and play. This Big Data can also be analysed for insights that lead to better decisions and strategic business moves.

Post 11: (Question 7) Limitations of traditional data analysis

As with all things there will always come limitations to data analysis due to the fact that it is created by humans and is subsequently subject to human error. Some of the limitations that you may come across would be that the data may be incomplete, whether it be missing values, or lack of a section of necessary data. This could severely limit the data's usability. Survey data can also be scrutinised due to the human component. People do not always provide accurate information through surveys and many are likely to not answer truthfully. For example if a person were asked how much alcohol they consume within a week they are likely to say less than their actual intake.

Blog For Big Data

Search This Blog